BingoCGN, a scalable and efficient graph neural network accelerator that enables inference of real-time, large-scale graphs through graph partitioning, has been developed by researchers at ...

When OpenAI released GPT-3, in June 2020, the neural network’s apparent grasp of language was uncanny. It could generate convincing sentences, converse with humans, and even autocomplete code.

Large language models evolved alongside deep-learning neural networks and are critical to generative AI. Here's a first look, including the top LLMs and what they're used for today.

GPT-3 has 175 billion parameters—the values in a neural network that store data and get adjusted as the model learns. Microsoft's Megatron-Turing language model has 530 billion parameters.

SpikeGPT also offers huge benefits for data security and privacy. With the language generator on a local device, data imputed into the systems are much more secure, protected from potential ...

Large language models such as ChaptGPT have proven to be able to produce remarkably intelligent results, but the energy and monetary costs associated with running these massive algorithms is sky high.